---
title: "**FIP606-Proyecto:** Análisis Exploratorio"
format: html
editor: visual
output:
distill::distill_article:
toc: true
toc_float: yes
code_folding: code
theme: theme.css
highlight: default
highlight_downlit: true
self_contained: true
date: "`r Sys.Date()`"
---
## **Preparación *Base de Datos***
-
#### ***Cargar paquetes de análisis***
```{r}
library (tidyverse)
library (gsheet)
library (cowplot)
library (patchwork)
library (ggthemes)
library (viridis)
library (epifitter)
library (ggplot2)
library ("writexl" )
library (nlme)
library (lme4)
library (DHARMa)
library (performance)
library (report)
library (emmeans)
library (multcompView)
library (multcomp)
library (corrplot)
library (see)
library (lubridate)
library (agridat)
library (cowplot)
library (agricolae)
library (sf)
library (lme4)
library (broom)
library (lattice)
library (car)
library (scales)
library (readxl)
library (dplyr)
library (knitr)
library (kableExtra)
library (easyanova)
library (tidyr)
library (PerformanceAnalytics)
library (magrittr)
library (car)
library (ggpubr)
library (rstatix)
library (reshape)
library (kableExtra)
library (formattable)
library (sjPlot)
library (sjlabelled)
library (sjmisc)
library (ggh4x)
library (gridExtra)
library (stringr)
library (epiR)
library (ggridges)
library (RColorBrewer)
library (DT)
library (gsheet)
```
-
#### ***Ajustar fecha como factor***
```{r}
DB_original <- read_excel ("DB_floración_01.xlsx" )
# Convertir la columna de fecha a formato POSIXct
DB_original$ Fecha <- as.POSIXct (DB_original$ Fecha, format = "%Y-%m-%dT%H:%M:%SZ" , tz = "UTC" )
# Convertir la columna de fecha a factor
DB_original$ Fecha <- as.factor (DB_original$ Fecha)
DB_original |>
DT:: datatable (
extensions = 'Buttons' ,
options = list (dom = 'Bfrtip' ,
buttons = c ('excel' , "csv" )))
```
-
#### ***Contar hojas con Roya y severidad total***
```{r}
# Seleccionar las columnas cuyo encabezado comienza con "S"
Hojas_Roya <- DB_original |>
select (starts_with ("S" ))
# Convertir las columnas seleccionadas a numéricas
Hojas_Roya<- Hojas_Roya |>
mutate (across (everything (), as.numeric))
# Crear una nueva columna que cuente cuántas columnas "S" tienen valores (no NA)
DB_original$ Hojas_Roya <- rowSums (! is.na (Hojas_Roya))
# Crear una nueva columna que sume los valores de las columnas "S" por fila
DB_original$ Severidad_total <- rowSums (Hojas_Roya, na.rm = TRUE )
DB_original |>
DT:: datatable (
extensions = 'Buttons' ,
options = list (dom = 'Bfrtip' ,
buttons = c ('excel' , "csv" )))
```
-
#### ***Asignar Tto al árbol***
Usar la funcion Mutate para crear nuevas columnas para crear una categoria para agrupar los arboles por tratamiento
```{r}
# Asignar nombres en función del rango de la columna Arbol
DB_original <- DB_original %>%
mutate (Parcela = case_when (
Arbol >= 1 & Arbol <= 80 ~ "Tto Fungicida" ,
Arbol >= 81 & Arbol <= 160 ~ "Tto Nuevo" ,
Arbol >= 161 & Arbol <= 240 ~ "Tto Testigo SA" ,
TRUE ~ NA_character_ # Asignar NA para valores fuera de los rangos especificados
))
DB_original |>
DT:: datatable (
extensions = 'Buttons' ,
options = list (dom = 'Bfrtip' ,
buttons = c ('excel' , "csv" )))
```
-
#### ***Calcular Incidencia, severidad , defoliación***
```{r}
DB_original <- DB_original |>
mutate (Incidencia = ((Nudos* 2 )/ Hojas_Roya),
Severidad = (Severidad_total/ Hojas_Roya),
Defoliacion = ( 100 - ((HP* 100 ) / (Nudos* 2 ))))
DB_original |>
DT:: datatable (
extensions = 'Buttons' ,
options = list (dom = 'Bfrtip' ,
buttons = c ('excel' , "csv" )))
```
-
#### ***Crear Base de datos***
```{r}
DB_analisis <- DB_original |>
select (Fecha,Parcela,Arbol,Rama,Nudos,Incidencia,Severidad,Defoliacion)
DB_analisis |>
DT:: datatable (
extensions = 'Buttons' ,
options = list (dom = 'Bfrtip' ,
buttons = c ('excel' , "csv" ))) |>
formatRound (c ('Incidencia' ,'Severidad' ,'Defoliacion' ), 2 )
```
### Preparación de la Base de datos Final
```{r}
dat<- read.csv2 ("DB_PAT104022.csv" )
dat |>
DT:: datatable (
extensions = 'Buttons' ,
options = list (dom = 'Bfrtip' ,
Buttons = c ('excel' , "csv" ))) |>
formatRound (c ('Inc_promedio' ,'Def_calculada' ,'Sev_total' ,'Severidad' ,'Sev_condicional' ), 2 )
```
Uso de la funcion select para convertir una tabla resumida
```{r}
CLR_ <- dat |>
select (Evaluacion,Time_,Time_E,Eva_E,Eva_,Parcela,Surco,Arbol_1,Arbol,Rep,Htotal,Inc_promedio,Def_calculada,Severidad,Sev_condicional)
CLR_ |>
DT:: datatable (
extensions = 'Buttons' ,
options = list (dom = 'Bfrtip' ,
Buttons = c ('excel' , "csv" )))
```
## Evaluaciones
- `Evaluacion 1 = (Mitaca_2021) Historico Sep/21`
- `Evaluacion 2 = (Principal_2022) Feb/22`
- `Evaluacion 3 = (Mitaca_2022) Floración Sep/22`
## Tratamientos
- Parcela =
- 1-`Tto Fungicida`
- 2- `Tto Fungicida Nuevo`
- 3- `Tto Testigo SA (Sin aplicación)`
## Variables
- `Arbol` = 1- 80
- `Rep` = 1-3
- `Nudos` = Número de nudos totales
- `Htotal` = Número de hojas totales presentes
- `Htotal_t` = Número de hojas totales teóricas (Nudos X 2)
- `Inc_promedio` = Porcentaje de hojas afectados por roya
- `Def_calculada` = Porcentaje de hojas faltantes en cada rama a partir de la marcación inicial y su conteo progresivo
- `Sev_total` = Sumatoria de valores de severidad de todas las hojas afectadas por la enfermedad
- `Severidad` = Proporcion de severidad total (sev_total) / Número de hojas totales presentes (Htotal)
- `Sev_condicional` = Proporcion de severidad total (sev_total) / Número de hojas afectadas por la enfermedad (Hroya)
- `Tx_Def` = (% de hojas que caen/día) = 0.0144 x incidencia
## ***Análisis Exploratorios***
-
## Visualización de Datos
-
### Evaluación por fecha
Comportamiento de las variables evaluadas sobre cada parcela en cada parcela de validación a través del tiempo.
-
### **Database**
```{r}
dat_ave<- CLR_ |>
group_by (Evaluacion,Time_,Time_E,Eva_E,Eva_,Parcela,Surco,Arbol_1,Arbol)|>
summarize (
Htotal= mean (Htotal,na.rm= TRUE ),
Incidencia = mean (Inc_promedio,na.rm= TRUE ),
Severidad = mean (Severidad,na.rm= TRUE ),
Defoliacion = mean (Def_calculada,na.rm= TRUE ))
dat_ave %>%
DT:: datatable (
extensions = 'Buttons' ,
options = list (dom = 'Bfrtip' ,
Buttons = c ('excel' , "csv" )))%>%
formatRound (c ('Htotal' ,'Incidencia' ,'Severidad' ,'Defoliacion' ), 2 )
```
-
## Evaluación (Tiempo)
```{r, fig.height=10, fig.width=25, warning=FALSE, message=FALSE}
Incidencia<-dat_ave %>%
ggplot(aes(Arbol_1,Surco,label = Arbol))+
geom_point(size = 5,shape=10,stroke = 1)+
geom_point(size = 5,alpha=1, aes(colour= Incidencia))+
scale_colour_distiller(palette = "Spectral",direction = -1,limits = c(0,100)) +
scale_y_discrete(limits=c("J","I","H","G","F","E","D","C","B","A"))+
scale_x_discrete(limits=c("1","2","3","4","5","6","7","8","9","10","11","12"),guide = guide_axis(position = "top")) +
facet_wrap(Parcela~Time_,ncol=9) +
theme_clean() +
theme(axis.text.x=element_blank(), #remove x axis labels
axis.ticks.x=element_blank(), #remove x axis ticks
axis.text.y=element_blank(), #remove y axis labels
axis.ticks.y=element_blank(), #remove y axis ticks
legend.title = element_text( face="bold",size = 20),
strip.text = element_text(size =15,face = "bold"),
plot.title = element_text(size =30,face="bold"),
plot.subtitle = element_text(size = 20),
plot.background = element_rect(colour = "white"),
legend.background = element_rect(colour = "white"),
legend.text = element_text(size = 15,face = c(rep("italic", 2), rep("plain", 2))),legend.position = "none") +
geom_text(size = 3,alpha=.9)+
labs(title = "A.Evaluación de Incidencia",x="Tiempo (ddfp)",y="Parcelas (Tratamientos)",
subtitle ="",caption ="")
Incidencia
```
```{r, fig.height=10, fig.width=25, warning=FALSE, message=FALSE}
Severidad<-dat_ave %>%
ggplot(aes(Arbol_1,Surco,label = Arbol))+
geom_point(size = 5,shape=10,stroke = 1)+
geom_point(size = 5,alpha=1, aes(colour= Severidad))+
scale_colour_distiller(palette = "Spectral",direction = -1,limits = c(0,5)) +
scale_y_discrete(limits=c("J","I","H","G","F","E","D","C","B","A"))+
scale_x_discrete(limits=c("1","2","3","4","5","6","7","8","9","10","11","12"),guide = guide_axis(position = "top")) +
facet_wrap(Parcela~Time_,ncol=9) +
theme_clean() +
theme(axis.text.x=element_blank(), #remove x axis labels
axis.ticks.x=element_blank(), #remove x axis ticks
axis.text.y=element_blank(), #remove y axis labels
axis.ticks.y=element_blank(), #remove y axis ticks
legend.title = element_text( face="bold",size = 20),
strip.text = element_text(size =15,face = "bold"),
plot.title = element_text(size =30,face="bold"),
plot.subtitle = element_text(size = 20),
plot.background = element_rect(colour = "white"),
legend.background = element_rect(colour = "white"),
legend.text = element_text(size = 15,face = c(rep("italic", 2), rep("plain", 2))),legend.position = "none") +
geom_text(size = 3,alpha=.9)+
labs(title = "A.Evaluación de Severidad",x="Tiempo (ddfp)",y="Parcelas (Tratamientos)",
subtitle ="",caption ="")
Severidad
```
```{r, fig.height=10, fig.width=25, warning=FALSE, message=FALSE}
Defoliacion<-dat_ave %>%
ggplot(aes(Arbol_1,Surco,label = Arbol))+
geom_point(size = 5,shape=10,stroke = 1)+
geom_point(size = 5,alpha=1, aes(colour= Defoliacion))+
scale_colour_distiller(palette = "Spectral",direction = -1,limits = c(0,100)) +
scale_y_discrete(limits=c("J","I","H","G","F","E","D","C","B","A"))+
scale_x_discrete(limits=c("1","2","3","4","5","6","7","8","9","10","11","12"),guide = guide_axis(position = "top")) +
facet_wrap(Parcela~Time_,ncol=9) +
theme_clean() +
theme(axis.text.x=element_blank(), #remove x axis labels
axis.ticks.x=element_blank(), #remove x axis ticks
axis.text.y=element_blank(), #remove y axis labels
axis.ticks.y=element_blank(), #remove y axis ticks
legend.title = element_text( face="bold",size = 20),
strip.text = element_text(size =15,face = "bold"),
plot.title = element_text(size =30,face="bold"),
plot.subtitle = element_text(size = 20),
plot.background = element_rect(colour = "white"),
legend.background = element_rect(colour = "white"),
legend.text = element_text(size = 15,face = c(rep("italic", 2), rep("plain", 2))),legend.position = "none") +
geom_text(size = 3,alpha=.9)+
labs(title = "A.Evaluación de Defoliación",x="Tiempo (ddfp)",y="Parcelas (Tratamientos)",
subtitle ="",caption ="")
Defoliacion
```
-
## Evaluación (Dinámica)
```{r, fig.height=5, fig.width=22, warning=FALSE, message=FALSE}
Plot1a<-dat %>%
group_by(Time_,Parcela)%>%
summarise(Incidencia=mean(Inc_promedio,na.rm=TRUE),sd=sd(Inc_promedio,na.rm=TRUE))%>%
mutate( se = sd / sqrt(length(Incidencia)))%>%
ggplot(aes(Time_,Incidencia, fill = Parcela, group= Parcela)) +
geom_rect(aes(xmin = 120 , xmax = 210, ymin = 0, ymax =100),fill = "#f7d8d8",alpha= 0.1) +
geom_rect(aes(xmin = 280 , xmax = 370, ymin = 0, ymax =100),fill = "#f7d8d8",alpha= 0.1) +
geom_area(position=position_identity(),alpha= 0.5)+
geom_errorbar(aes(ymin=Incidencia-se, ymax=Incidencia+se), width=0.4, alpha=0.9, size=.8,position=position_dodge(0.05))+
geom_hline(yintercept=15,linetype="dashed", color = "blue",size=1) +
facet_wrap(~Parcela,ncol =3) +
theme_clean() +
theme(axis.text = element_text(size = 8),
axis.text.x = element_text( size =10,angle = 90),
axis.title = element_text(size = 10),
strip.text.x=element_text(face="bold",size =10,margin=margin(1,0,1,0)),
plot.background = element_rect(colour = "white"),
legend.background = element_rect(colour = "white"),
legend.title = element_text( face="bold",size = 10),
legend.text = element_text( size = 10),
plot.title = element_text(size = 15,face="bold"),
plot.subtitle = element_text(size = 15),
legend.position = "none" ) +
scale_fill_manual(values = c( "Tto Fungicida"="#669933", "Tto Nuevo"="#FFCC66","Tto Testigo SA"="#990000"))+
scale_x_continuous(breaks=c(0,30,60,90,120,150,180,210,240,270,300,330,360,390,420,450))+
ylim(-5, 100) +
labs(
fill = "Tratamiento", x = "Días de Evaluación (ddfp)",
y = "% Incidencia",
title = "A. Dinámica Incidencia",subtitle =""
)
```
```{r, fig.height=5, fig.width=22, warning=FALSE, message=FALSE}
Plot2a<-dat %>%
group_by(Time_,Parcela)%>%
summarise(Severidad=mean(Sev_condicional,na.rm=TRUE),sd=sd(Sev_condicional,na.rm=TRUE))%>%
mutate( se = sd / sqrt(length(Severidad)))%>%
ggplot(aes(Time_,Severidad, fill = Parcela, group= Parcela)) +
geom_rect(aes(xmin = 120 , xmax = 210, ymin = 0, ymax =7),fill = "#f7d8d8",alpha= 0.1) +
geom_rect(aes(xmin = 280 , xmax = 370, ymin = 0, ymax =7),fill = "#f7d8d8",alpha= 0.1) +
geom_area(position=position_identity(),alpha= 0.5)+
geom_errorbar(aes(ymin=Severidad-se, ymax=Severidad+se), width=0.4, alpha=0.9, size=.8,position=position_dodge(0.05))+
geom_hline(yintercept=2,linetype="dashed", color = "blue",size=1) +
facet_wrap(~Parcela,ncol =3) +
theme_clean() +
theme(axis.text = element_text(size = 8),
axis.text.x = element_text( size =10,angle = 90),
axis.title = element_text(size = 10),
strip.text.x=element_text(face="bold",size =10,margin=margin(1,0,1,0)),
plot.background = element_rect(colour = "white"),
legend.background = element_rect(colour = "white"),
legend.title = element_text( face="bold",size = 10),
legend.text = element_text( size = 10),
plot.title = element_text(size = 15,face="bold"),
plot.subtitle = element_text(size = 15),
legend.position = "none" ) +
scale_fill_manual(values = c( "Tto Fungicida"="#669933", "Tto Nuevo"="#FFCC66","Tto Testigo SA"="#990000"))+
scale_x_continuous(breaks=c(0,30,60,90,120,150,180,210,240,270,300,330,360,390,420,450))+
ylim(-1, 7) +
labs(
fill = "Tratamiento", x = "Días de Evaluación (ddfp)",
y = "% Severidad",
title = "B. Dinámica Severidad",subtitle =""
)
```
```{r, fig.height=5, fig.width=22, warning=FALSE, message=FALSE}
Plot3a<-dat %>%
group_by(Time_,Parcela)%>%
summarise(Defoliacion= median(Def_calculada,na.rm=TRUE),sd=sd(Def_calculada,na.rm=TRUE))%>%
mutate( se = sd / sqrt(length(Defoliacion)))%>%
ggplot(aes(Time_,Defoliacion, fill = Parcela, group= Parcela)) +
geom_rect(aes(xmin = 120 , xmax = 210, ymin = 0, ymax =100),fill = "#f7d8d8",alpha= 0.1) +
geom_rect(aes(xmin = 280 , xmax = 370, ymin = 0, ymax =100),fill = "#f7d8d8",alpha= 0.1) +
geom_area(position=position_identity(),alpha= 0.5)+
geom_errorbar(aes(ymin=Defoliacion-se, ymax=Defoliacion+se), width=0.4, alpha=0.9, size=.8,position=position_dodge(0.05))+
geom_hline(yintercept=50,linetype="dashed", color = "blue",size=1) +
facet_wrap(~Parcela,ncol =3) +
theme_clean() +
theme(axis.text = element_text(size = 8),
axis.text.x = element_text( size =10,angle = 90),
axis.title = element_text(size = 10),
strip.text.x=element_text(face="bold",size =10,margin=margin(1,0,1,0)),
plot.background = element_rect(colour = "white"),
legend.background = element_rect(colour = "white"),
legend.title = element_text( face="bold",size = 10),
legend.text = element_text( size = 10),
plot.title = element_text(size = 15,face="bold"),
plot.subtitle = element_text(size = 15),
legend.position = "none" ) +
scale_fill_manual(values = c( "Tto Fungicida"="#669933", "Tto Nuevo"="#FFCC66","Tto Testigo SA"="#990000"))+
scale_x_continuous(breaks=c(0,30,60,90,120,150,180,210,240,270,300,330,360,390,420,450))+
ylim(0, 100) +
labs(
fill = "Tratamiento", x = "Días de Evaluación (ddfp)",
y = "% Defoliación",
title = "C. Dinamica Defoliación",subtitle =""
)
```
```{r, fig.height=10, fig.width=15, warning=FALSE, message=FALSE}
Plot_Lote<- (Plot1a + Plot2a + Plot3a + plot_layout(ncol = 1))
Plot_Lote
#ggexport(Plot_Lote,filename = "Fig1_MQR104024_Dinamic-_lote_full.pdf", width = 25 , height = 15)
```
-
## Dispersión (Incidencia)
```{r, fig.height=5, fig.width=8, warning=FALSE, message=FALSE}
library(ggthemes)
dat_ave |>
ggplot(aes(Eva_, Incidencia, color = Parcela))+
geom_rect(aes(xmin = 4 , xmax = 7, ymin = 0, ymax =100),fill = "#f7d8d8",alpha = 0.3,color = NA) +
geom_rect(aes(xmin = 9 , xmax = 12, ymin = 0, ymax =100),fill = "#f7d8d8",alpha = 0.3,color = NA) +
geom_jitter(size=2,alpha=0.3)+
geom_hline(yintercept=30,linetype="dashed", color = "blue",size=1) +
stat_summary(fun.data = mean_se,size=.2,
color = "black")+
theme_clean()+
theme(axis.text = element_text(size = 8),
axis.text.x = element_text( size =10),
axis.title = element_text(size = 10),
strip.text.x=element_text(face="bold",size =10,margin=margin(1,0,1,0)),
plot.background = element_rect(colour = "white"),
legend.background = element_rect(colour = "white"),
legend.title = element_text( face="bold",size = 10),
legend.text = element_text( size = 10),
plot.title = element_text(size = 15,face="bold"),
plot.subtitle = element_text(size = 15),
legend.position = "none" ) +
scale_color_manual(values = c( "#669933","#FFCC66","#990000"))+
facet_wrap(~Parcela, nrow = 3,)+
ylim(0,100)+
scale_x_continuous(breaks = seq(from = 1, to = 15, by = 1))+
labs(
x = "Evaluaciónes",
y = "% Incidencia",
title = "A. Dispersión Incidencia",subtitle =""
)
```
-
## Dispersión (Severidad)
```{r, fig.height=5, fig.width=8, warning=FALSE, message=FALSE}
dat_ave |>
ggplot(aes(Eva_, Severidad, color = Parcela))+
geom_rect(aes(xmin = 4 , xmax = 7, ymin = 0, ymax =10),fill = "#f7d8d8",alpha = 0.1,color = NA) +
geom_rect(aes(xmin = 9 , xmax = 12, ymin = 0, ymax =10),fill = "#f7d8d8",alpha = 0.1,color = NA) +
geom_jitter(size=2,alpha=0.3)+
geom_hline(yintercept=5,linetype="dashed", color = "blue",size=1) +
stat_summary(fun.data = mean_se,size=.2,
color = "black")+
theme_clean()+
theme(axis.text = element_text(size = 8),
axis.text.x = element_text( size =10),
axis.title = element_text(size = 10),
strip.text.x=element_text(face="bold",size =10,margin=margin(1,0,1,0)),
plot.background = element_rect(colour = "white"),
legend.background = element_rect(colour = "white"),
legend.title = element_text( face="bold",size = 10),
legend.text = element_text( size = 10),
plot.title = element_text(size = 15,face="bold"),
plot.subtitle = element_text(size = 15),
legend.position = "none" ) +
scale_color_manual(values = c( "#669933","#FFCC66","#990000"))+
facet_wrap(~Parcela, nrow = 3,)+
ylim(0,10)+
scale_x_continuous(breaks = seq(from = 1, to = 15, by = 1))+
labs(
x = "Evaluaciónes",
y = "% Severidad",
title = "B. Dispersión Severidad",subtitle =""
)
```
-
## Dispersión (Defoliación)
```{r, fig.height=5, fig.width=8, warning=FALSE, message=FALSE}
dat_ave |>
ggplot(aes(Eva_, Defoliacion, color = Parcela))+
geom_rect(aes(xmin = 4 , xmax = 7, ymin = 0, ymax =100),fill = "#f7d8d8",alpha = 0.1,color = NA) +
geom_rect(aes(xmin = 9 , xmax = 12, ymin = 0, ymax =100),fill = "#f7d8d8",alpha = 0.1,color = NA) +
geom_jitter(size=2,alpha=0.3)+
geom_hline(yintercept=50,linetype="dashed", color = "blue",size=1) +
stat_summary(fun.data = mean_se,size=.2,
color = "black")+
theme_clean()+
theme(axis.text = element_text(size = 8),
axis.text.x = element_text( size =10),
axis.title = element_text(size = 10),
strip.text.x=element_text(face="bold",size =10,margin=margin(1,0,1,0)),
plot.background = element_rect(colour = "white"),
legend.background = element_rect(colour = "white"),
legend.title = element_text( face="bold",size = 10),
legend.text = element_text( size = 10),
plot.title = element_text(size = 15,face="bold"),
plot.subtitle = element_text(size = 15),
legend.position = "none" ) +
scale_color_manual(values = c( "#669933","#FFCC66","#990000"))+
facet_wrap(~Parcela, nrow = 3,)+
ylim(0,100)+
scale_x_continuous(breaks = seq(from = 1, to = 15, by = 1))+
labs(
x = "Evaluaciónes",
y = "% Defoliación",
title = "C. Dispersión Defoliación",subtitle =""
)
```
-
## Descriptiva Incidencia (Periodo Critico)
```{r}
CLR_descriptivas_inc <- dat_ave |>
filter ((Eva_ >= 4 & Eva_ <= 7 ) | (Eva_ >= 9 & Eva_ <= 12 )) |>
group_by (Parcela,Evaluacion) |>
summarise (
mean_inc = mean (Incidencia,na.rm= TRUE ),
sd_inc = sd (Incidencia,na.rm= TRUE ),
var_inc = var (Incidencia,na.rm= TRUE ),
n = n (),
se_inc = sd_inc / sqrt (n - 1 ),
ci = se_inc * qt (0.05 , df = n - 1 )
)
CLR_descriptivas_inc |>
DT:: datatable (
extensions = 'Buttons' ,
options = list (dom = 'Bfrtip' ,
buttons = c ('excel' , "csv" ))) |>
formatRound (c ('mean_inc' , 'sd_inc' , 'var_inc' ,'se_inc' ,'ci' ), 2 )
```
-
## Descriptiva Severidad (Periodo Critico)
```{r}
CLR_descriptivas_sev <- dat_ave |>
filter ((Eva_ >= 4 & Eva_ <= 7 ) | (Eva_ >= 9 & Eva_ <= 12 )) |>
group_by (Parcela,Evaluacion) |>
summarise (
mean_sev = mean (Severidad,na.rm= TRUE ),
sd_sev = sd (Severidad,na.rm= TRUE ),
var_sev = var (Severidad,na.rm= TRUE ),
n = n (),
se_sev = sd_sev / sqrt (n - 1 ),
ci = se_sev * qt (0.05 , df = n - 1 )
)
CLR_descriptivas_sev |>
DT:: datatable (
extensions = 'Buttons' ,
options = list (dom = 'Bfrtip' ,
buttons = c ('excel' , "csv" ))) |>
formatRound (c ('mean_sev' , 'sd_sev' , 'var_sev' ,'se_sev' ,'ci' ), 2 )
```
-
## Descriptiva Defoliación(Periodo Critico)
```{r}
CLR_descriptivas_def <- dat_ave |>
filter ((Eva_ >= 4 & Eva_ <= 7 ) | (Eva_ >= 9 & Eva_ <= 12 )) |>
group_by (Parcela,Evaluacion) |>
summarise (
mean_def = mean (Defoliacion,na.rm= TRUE ),
sd_def = sd (Defoliacion,na.rm= TRUE ),
var_def = var (Defoliacion,na.rm= TRUE ),
n = n (),
se_def = sd_def / sqrt (n - 1 ),
ci = se_def * qt (0.05 , df = n - 1 )
)
CLR_descriptivas_def |>
DT:: datatable (
extensions = 'Buttons' ,
options = list (dom = 'Bfrtip' ,
buttons = c ('excel' , "csv" ))) |>
formatRound (c ('mean_def' , 'sd_def' , 'var_def' ,'se_def' ,'ci' ), 2 )
```
```{r}
CLR_inc <- CLR_ |>
filter ((Eva_ >= 4 & Eva_ <= 7 ) | (Eva_ >= 9 & Eva_ <= 12 )) |>
group_by (Arbol) |>
ggplot (aes (Parcela, Inc_promedio, fill = Parcela)) +
geom_boxplot (alpha = .5 )+
stat_summary (fun.data = "mean_se" ,colour = "red" )+
facet_wrap (~ Evaluacion)+
theme_clean ()+
theme (axis.text = element_text (size = 8 ),
axis.text.x = element_text ( size = 10 ),
axis.title = element_text (size = 10 ),
strip.text.x= element_text (face= "bold" ,size = 10 ,margin= margin (1 ,0 ,1 ,0 )),
plot.background = element_rect (colour = "white" ),
legend.background = element_rect (colour = "white" ),
legend.title = element_text ( face= "bold" ,size = 10 ),
legend.text = element_text ( size = 10 ),
plot.title = element_text (size = 15 ,face= "bold" ),
plot.subtitle = element_text (size = 15 ),
legend.position = "none" ) +
scale_fill_manual (values = c ( "#669933" ,"#FFCC66" ,"#990000" ))+
labs (
y = "% Incidencia" ,
title = "A. Boxplot Incidencia" ,subtitle = ""
)
```
```{r}
CLR_sev <- CLR_ |>
filter ((Eva_ >= 4 & Eva_ <= 7 ) | (Eva_ >= 9 & Eva_ <= 12 )) |>
group_by (Arbol) |>
ggplot (aes (Parcela, Sev_condicional, fill = Parcela)) +
geom_boxplot (alpha = .5 )+
stat_summary (fun.data = "mean_se" ,colour = "red" )+
facet_wrap (~ Evaluacion)+
theme_clean ()+
theme (axis.text = element_text (size = 8 ),
axis.text.x = element_text ( size = 10 ),
axis.title = element_text (size = 10 ),
strip.text.x= element_text (face= "bold" ,size = 10 ,margin= margin (1 ,0 ,1 ,0 )),
plot.background = element_rect (colour = "white" ),
legend.background = element_rect (colour = "white" ),
legend.title = element_text ( face= "bold" ,size = 10 ),
legend.text = element_text ( size = 10 ),
plot.title = element_text (size = 15 ,face= "bold" ),
plot.subtitle = element_text (size = 15 ),
legend.position = "none" ) +
scale_fill_manual (values = c ( "#669933" ,"#FFCC66" ,"#990000" ))+
labs (
y = "% Severidad" ,
title = "B. Boxplot Severidad" ,subtitle = ""
)
```
```{r}
CLR_def <- CLR_ |>
filter ((Eva_ >= 4 & Eva_ <= 7 ) | (Eva_ >= 9 & Eva_ <= 12 )) |>
group_by (Arbol) |>
ggplot (aes (Parcela, Def_calculada, fill = Parcela)) +
geom_boxplot (alpha = .5 )+
stat_summary (fun.data = "mean_se" ,colour = "red" )+
facet_wrap (~ Evaluacion)+
theme_clean ()+
theme (axis.text = element_text (size = 8 ),
axis.text.x = element_text ( size = 10 ),
axis.title = element_text (size = 10 ),
strip.text.x= element_text (face= "bold" ,size = 10 ,margin= margin (1 ,0 ,1 ,0 )),
plot.background = element_rect (colour = "white" ),
legend.background = element_rect (colour = "white" ),
legend.title = element_text ( face= "bold" ,size = 10 ),
legend.text = element_text ( size = 10 ),
plot.title = element_text (size = 15 ,face= "bold" ),
plot.subtitle = element_text (size = 15 ),
legend.position = "none" ) +
scale_fill_manual (values = c ( "#669933" ,"#FFCC66" ,"#990000" ))+
labs (
y = "% Defoliaci" ,
title = "C. Boxplot Defoliación" ,subtitle = ""
)
```
```{r, fig.height=10, fig.width=10, warning=FALSE, message=FALSE}
Plot_Boxplot<- (CLR_inc + CLR_sev + CLR_def + plot_layout(ncol = 1))
Plot_Boxplot
#ggexport(Plot_Lote,filename = "Fig1_MQR104024_Dinamic-_lote_full.pdf", width = 25 , height = 15)
```
Analysis carried out in the FIP606 Copyrigth Gustavo Marin / Gabriela Rivadeneira © 2024
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